The first part of the course covers basic concepts in probability; the second part renewal and regenerative processes including Markov chains; and the last part Martingales and Brownian motion. Throughout, theoretic results are applied to the analysis of queues. Students are expected to have some background in probability (e.g., IEMS 202-0) and stochastic processes; no measure theory background is required.